在R里面使用dplyr对表格进行计算、筛选等操作 我的需求:基因表达差异分析结果的表格,每行是一个基因,不同的列分别表示表达值、Fold Change、P value、Q value等信息,如果要根据基因名称筛选出特定的行,或者针对P value进行数据转化并计算出-log10(P value),可以用dplyr进行实现。 下文转载自:omicsgene https://w...
date_price <- select(order_tbl,orderdate, totalprice) date_price # rename column name at the same time date_price2 <- select(order_tbl,date = orderdate, price = totalprice) date_price2 # select starts with order column name Start_With_Order <- select(order_tbl,starts_with("order",i...
bind_rows() works correctly with NULL arguments and an .id argument (#2056), and also for zero-column data frames (#2175). Breaking change: bind_rows() and combine() are more strict when coercing. Logical values are no longer coerced to integer and numeric. Date, POSIXct and other in...
library(dplyr) # Combine vectors into data frame(optimized) data_frame(a=1:3,b=4:6) # Order rows by values od a column(low to high) arrange(mtcars,mpg) #Order rows by values of a column(high to low) arrange(mtcars,desc(mpg)) #Rename the columns of a data frame rename(tb,y=...
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I had the same problem trying to get data into knn and it telling me that subsets of the wonky import weren't the same length. I ended up creating a for loop to dump each column into a new data frame one by one. The new data frame was clean. ...
As you can see, Peter in 2001 and Kate in 2001 are both marked as "1" in the "change" column because they replaced "John" and "Fred" in 2000-CA and 2000-NY, respectively. I've been looking at using some lag methods, but it seems to just look at the previous row, not by stat...
Change to put pop on the x-axis and gdpPercap on the y-axisggplot(gapminder_1952, aes(x = pop, y = gdpPercap)) +geom_point() 3.1 x坐标取对数 zheyang >library(gapminder) >library(dplyr) >library(ggplot2) > > gapminder_1952 <- gapminder %>%filter(year ==1952) ...
ReshapingData-Changethelayoutofadataset SubsetObservations(Rows)SubsetVariables(Columns) FMA Eachvariableissaved initsowncolumn FMA Eachobservationis savedinitsownrow Inatidy dataset: & TidyData-AfoundationforwranglinginR TidydatacomplementsR’svectorized ...
Introduction In my last post we looked at how to slice a data.table by group to obtain the rows for which a particular column in that group is at its maximum value using the excellent data.table package. In this post, we will be taking a look at how to p